A business may present content, including advertisements, to users. For example, a business might receive advertisement information from merchants (e.g., text or image information) and in turn present advertisements to users, along with other content, via web pages. In this case, the merchant may provide payment to the business based at least in part on how many users viewed (and/or responded to) the advertisements.
For various reasons, users may respond to different layouts, combinations, and/or selections of advertisements in different ways. For example, displaying text advertisements above image advertisements might turn out to be less effective as compared to displaying them below. Similarly, placing one type of advertisement next to another type of advertisement might decrease user response to both advertisements. Also note that similar displays might be received differently depending on the type of user (e.g., the user's age and whether the user is male or female), the time of day, or any of a number of other factors. Because a business may receive payment based at least in part on user reaction to a display, it may be advantageous to select and/or adjust the display to improve user reaction. Manually monitoring user reaction to select and/or adjust an appropriate display, however, can be an inefficient process. This might be especially true when the business is associated with a substantial number of displays. Therefore an automated process to monitor and select the appropriate display that yields the highest net effective revenue may be desired.